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generate-connector-spec

Generate connector_spec.yaml from Python source code with authentication parameters.

60|116|Updated Nov 13, 2025
Search Tags:#authentication#configuration#yaml#spec#connector#data source
One-click install
npx skills add https://github.com/databrickslabs/lakeflow-community-connectors --skill generate-connector-spec
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: generate-connector-spec
Source: https://github.com/databrickslabs/lakeflow-community-connectors/tree/main/.claude/skills/generate-connector-spec
Command: npx skills add https://github.com/databrickslabs/lakeflow-community-connectors --skill generate-connector-spec

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the creation of the connector_spec.yaml file, which is crucial for defining how a data connector interacts with a source system, including its authentication methods and allowed options.

Core Features & Use Cases

  • Automated YAML Generation: Creates the connector_spec.yaml file based on the connector's Python implementation.
  • Authentication Parameter Definition: Accurately identifies and structures connection parameters, supporting both single and multiple authentication methods.
  • External Options Allowlisting: Compiles a list of table-specific options used in read methods.
  • Use Case: After implementing a new data connector for a SaaS product, use this Skill to generate its specification file, ensuring consistent and correct configuration for users.

Quick Start

Use the generate-connector-spec skill to create the connector spec YAML for the 'github' connector.

Frequently Asked Questions about generate-connector-spec

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a connector spec YAML file for a new data source?▼

A connector spec YAML defines how a data connector interacts with a source system by specifying authentication methods and allowed configuration options. This specification is essential for configuring data ingestion pipelines and ensuring proper, consistent data source interaction.

How does connector specification generation handle multiple authentication methods?▼

Yes, you can define table-specific options in the YAML spec. The generation process compiles an external options allowlist by analyzing table-specific options used in the connector's Python read methods, ensuring correct data source interaction configurations.

Do I need Python source code to generate a connector spec?▼

Automated YAML generation is preferred over manual configuration because it analyzes the connector's Python implementation to accurately identify authentication parameters and compile table-specific options. This ensures consistent and correct configuration without manual specification errors.

What are the limitations of generating a connector spec from Python source code?▼

A limitation of generating a connector spec from Python source code is that it relies on analyzing the existing implementation to determine parameters. If the Python code lacks explicit authentication structures or read methods, the generated YAML allowlist may be incomplete.

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